Causal association between kynurenine and depression investigated using two-sample mendelian randomization

As research progresses, the intricate metabolic connections between depression and tryptophan, as well as kynurenine (KYN), have become increasingly evident. In studies investigating the relationship between KYN and depression, the conclusions reached thus far have been inconsistent. Therefore, we propose employing a two-sample mendelian randomization (MR) approach to further elucidate the relationship between KYN and depression. We utilized extensive data from large-scale genome-wide association studies to identify single nucleotide polymorphisms that act as instrumental variables for kynurenine and depression in European ancestry populations, ensuring compliance with MR assumptions. We employed five MR algorithms, namely, weighted median, MR-Egger, inverse variance weighted (IVW), simple mode, and weighted mode, with IVW as the primary analysis method. Sensitivity tests were conducted using Cochran’s Q test, MR-Egger intercept test, MR Pleiotropy Residual Sum and Outlier, and Leave-one-out analysis.The IVW analysis revealed that each standard deviation increase in kynurenine corresponded to a 1.4-fold increase in the risk of depression (OR = 1.351, 95% CI 1.110–1.645, P = 0.003). The direction of the effect size (positive or negative) was consistent with the findings from the other four algorithms. Sensitivity tests indicated no heterogeneity or horizontal pleiotropy among the instrumental variables. Elevated levels of kynurenine have a causal relationship with an increased risk of developing depression.


MR analysis
MR analysis was performed using five methods: Weighted median (WM), MR-Egger, inverse variance weighted (IVW), simple mode, and weighted mode.The IVW method served as the primary analysis.A significant result from the IVW analysis (P < 0.05) along with consistent effect directions (positive or negative) across the other four methods supports the inference of a causal relationship.This means that the results of these five algorithms are consistent, supporting the remarkable results of IVW.The IVW algorithm is a commonly used two-sample MR analysis method, which can make full use of the sample information of each study, thereby improving statistical power.When using other algorithms, some preprocessing of the data may be required, such as removing outliers, performing data transformation, etc., and these preprocessing may affect the results.The IVW algorithm requires less data and does not require special preprocessing, so the results may be more accurate.In addition, if the sample size is small or the sample distribution is uneven, the results of other algorithms may be more affected, and the IVW algorithm can maintain high statistical power in this case.When all SNPs adhere to the assumptions of MR, only under such conditions can the inverse variance weighted (IVW) method yield accurate estimates of causal relationships.The WM method leverages a majority of effective instrumental variables (IVs) for causal inference.MR-Egger, on the other hand, allows the inclusion of IVs that exhibit pleiotropy.The intercept is used

Sensitivity analysis
Sensitivity tests were carried out to gauge the robustness of the findings.Cochran's Q test was implemented to assess the heterogeneity among SNPs, with a P-value of less than 0.05 indicating significant heterogeneity.
Techniques such as the MR-Egger intercept test and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) were deployed to investigate horizontal pleiotropy.If the intercept in the MR-Egger intercept test is statistically significant (P < 0.05), it implies a significant presence of pleiotropy.If the P-value of the MR-PRESSO result falls below 0.05, it suggests that the MR analysis presents considerable horizontal pleiotropy, which means that the IVs can directly influence the outcome without acting through the exposure factor.A leave-one-out analysis was conducted, which involved the sequential exclusion of each SNP to examine the impact on the combined effect of the remaining SNPs.Any notable alterations in the results due to the exclusion of a particular SNP suggests that the SNP has a substantial influence on the result, which infringes on the assumption of MR.The final results were presented using scatter plots, forest plots, and funnel plots.

Institutional review board statement
This study was based on a published database and did not require ethical approval.

Results
The MR analysis examined the causal relationship between KYN as the exposure and depression as the outcome.
After applying the selection criteria, a total of 17 SNPs were identified as IVs that met the MR assumptions.Eight SNPs with F < 10 were excluded from the analysis, namely, rs3809198 (F = 0.83), rs16924894 (F = 1.46), rs16974854 (F = 1.74), rs11593042 (F = 3.50), rs511797 (F = 4.70), rs3789978 (F = 6.28), rs6575634 (F = 9.63), and rs2651516 (F = 9.97).No SNPs significantly associated with depression (P < 5 × 10 -8 ) were found among the KYN SNPs extracted from the depression GWAS data.Palindromic variants were not detected.However, the SNP rs3184504 was identified as confounded by body mass index, which has been causally linked to depression in previous MR studies.Hence, this SNP was removed from the analysis 14 .Detailed results are presented in Table 2.
The IVW method, serving as the primary analysis, indicated that each standard deviation increase in KYN was associated with an approximately 1.4-fold increase in the risk of depression (OR = 1.351, 95% CI 1.110-1.645,P = 0.003).The effect directions from the other four methods were consistent with IVW.Further details can be found in Table 3.
Sensitivity analysis demonstrated no heterogeneity among the SNPs, as indicated by Cochran's Q test (IVW: Q = 12.982, P = 0.674; MR-Egger: Q = 12.905, P = 0.610).The MR-Egger intercept test showed no evidence of horizontal pleiotropy (Intercept = − 0.001, P = 0.785).MR-PRESSO analysis did not identify any outliers (P = 0.719).The scatter plot illustrated the stability of the SNPs strongly associated with both KYN and depression (Fig. 1).The funnel plot displayed a symmetrical distribution of the SNPs, indicating no pleiotropy in the MR analysis www.nature.com/scientificreports/(Fig. 2).Leave-one-out analysis demonstrated that the exclusion of individual SNPs did not significantly impact the overall results (Fig. 3).

Discussion
Emerging evidence points to the involvement of KYN, a metabolite of tryptophan, in the development of depression, with disruptions in the kynurenine pathway playing a significant role in the etiology of depression 15,16 .However, the relationship between KYN and depression remains unclear.This study endeavored to explore the causal relationship between KYN and depression using a two-sample MR approach.The research results provide robust evidence, indicating that an elevation in KYN levels significantly increases the risk of developing depression.
The chronic inflammation hypothesis of depression has garnered substantial literature support, positing depression as a neuroimmune disorder where the activation of the immune system plays a pivotal role in the onset and progression of depression [17][18][19] .Neuroinflammation is implicated in the regulation of the tryptophankynurenine (TRP-KYN) pathway, particularly modulated by various pro-inflammatory cytokines such as TNF-α, IL-6, INF-γ 20,21 .Previous observational studies have reported associations between abnormalities in tryptophankynurenine metabolism and depressive disorders, particularly in scenarios involving inflammation.These studies align with our findings, which demonstrate an increase in KYN levels in individuals with depression 9,11,[22][23][24][25] .Some scholars have proposed a novel subtype of depression termed "immune-metabolic depression", wherein alterations in inflammation, metabolism, and bioenergetic pathways are observed in the majority of individuals with depression 26 .Regrettably, given the current unavailability of GWAS data for immune-metabolic depression, we are unable to elucidate the causal relationship between KYN and immune-metabolic depression.If GWAS data for immune-metabolic depression and non-immune-metabolic depression become accessible in the future, a renewed MR analysis could be conducted to investigate the causal relationship between KYN and these two subtypes of depression.KYN may lean towards having a causal relationship with immune-metabolic depression.Future research might explore common genetic features between KYN and immune-metabolic depression in this direction.
Potential mechanisms underlying the link between KYN and depression may involve the induction of depressive-like behavior through increased expression of Nod-like receptor protein 2 (NLPR2) in astrocytes by KYN, mediated by proinflammatory cytokines 4 .Cytokines such as IL-1β, IL-6, and TNF-α can also inhibit the    conversion of KYN to 5-HT by activating the kynurenine pathway, resulting in a decrease in 5-HT synthesis and the manifestation of depressive symptoms 27 .Several limitations should be considered in interpreting the findings of this study.First, the data used in this analysis were derived from individuals of European ancestry, potentially limiting the generalizability of the results to other populations.Second, while various sensitivity analyses were conducted to assess the assumptions of the MR study, it is challenging to completely rule out the possibility of pleiotropy influencing the instrumental variables.Last, the sample size of the available GWAS datasets was limited, emphasizing the need for further research using larger and more diverse datasets.

Conclusions
In this study, we utilized a two-sample MR approach to investigate the causal relationship between KYN and depression.The findings provide compelling genetic evidence supporting a causal link between elevated levels of KYN and an increased risk of depression.This provides genetic evidence for understanding the etiological mechanisms of depression and potential interventions.Specifically, it prompts further exploration into whether the dysregulation of the KYN metabolic pathway is a pathogenic mechanism for depression, whether KYN can serve as a potential therapeutic target, or whether it can be used as a diagnostic or screening marker for depression.However, these findings warrant further investigation and validation.

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Sample sizes, age groups and the proportion of males and females of the study cohorts.†Thedistribution of age and gender not reported for the depression cohorts; PGC, Psychiatric Genomics Consortium; KORA, Cooperative Health Research in the Region of Augsburg.

Table 2 .
Information on the SNPs for the final screened KYN (n = 17).SNP, single nucleotide polymorphism; Gene, Gene information is derived from Phenoscanner; β, effector value; SE, standard error; P a , the P value of depression SNPs.

Table 3 .
Results of the five MR algorithms.WM, Weighted median; IVW, inverse variance weighted.